SISCA OM fit report

Data Scenario and Model Hypothesis

SISCAH MP application for SOGHerring data.

Data Scenario: SOG

Model Hypothesis: DIM_2024

Final phase convergence diagnostics

Max Gradient: 5.9003771^{-4}

Objective Function value: -639.5216521

Time to fit model: 5.89

PD Hessian: TRUE

No. of Non-finite SEs: 0

Biomass estimate and TAC advice

Figure 1: Time series of spawning biomass with scaled spawn indices (top), recruitments (second row), natural mortality (third row), and harvest rates (bottom row) for substocks of SOGHerring. Stocks are, from left to right,SOG.

Figure 2: SOG Herring management procedure harvest control rule (line) and TAC advice (annotation).

## NULL

Model goodness of fit

Table 1: Estimated standard deviations for observational data. The first three columns show age data sampling error standard deviations from the logistic-normal compositional likelihood function, and the last column shows spawn survey index standard deviations on the log scale.

	\(\tau^{age}_{Red}\)	\(\tau^{age}_{SR}\)	\(\tau^{age}_{Gn}\)	\(\tau^{surv}_{Su}\)	\(\tau^{surv}_{D}\)	\(\sigma_{R,eff}\)	\(\sigma_{M,eff}\)
SOG	0.659	0.308	0.529	0.346	0.259	0.6	0.385

Figure 3: Model fits to spawn indices.

Figure 4: Average model fits to age data. Stocks are left to right, and gears are top to bottom.